The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
A clear, concise, simple yet powerful and efficient API for deep learning.
Infrastructures™ for Machine Learning Training/Inference in Production.
A lightweight deep learning library
One-Stop System for Machine Learning.
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.
A deep learning framework created from scratch with Python and NumPy
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
[Experimental] Graph and Tensor Abstraction for Deep Learning all in Common Lisp
[MICCAI'24] Official implementation of "BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection".
[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
以jax为后端的类似keras的框架
[CVPR 2024] CFAT: Unleashing Triangular Windows for Image Super-resolution
NumPy-based Dynamic Deep Learning Framework
Explore the latest AI Agent Toolkit!
Deep Learning framework in C++/CUDA that supports symbolic/automatic differentiation, dynamic computation graphs, tensor/matrix operations accelerated by GPU and implementations of various state-of-the-art graph neural networks and other Machine Learning models including Covariant Compositional Networks For Learning Graphs [Risi et al]
🌳 An educational modern C++ deep learning framework supporting CUDA
RusTorch is a production-grade deep learning framework re-imagined in Rust. It combines the usability you love from PyTorch with the performance, safety, and concurrency guarantees of Rust. Say goodbye to GIL locks, GC pauses, and runtime errors. Say hello to RusTorch.
Facial Expression Recognition (FER) for Mental Health Detection applies AI models like Swin Transformer, CNN, and ViT for detecting emotions linked to anxiety, depression, PTSD, and OCD. It focuses on AI for mental health, emotion detection using OpenCV Python, and real-time applications in healthcare and HR systems.
Flow-based data pre-processing for deep learning
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